User location data and location history can provide a range of valuable insights and capabilities to marketers. Online-to-offline attribution is only one of them.
After several years of trials and testing, enterprise marketers and brands are starting to see how versatile location data is and embrace its many use cases. As evidence of this, within one week, three location data providers (CARTO, Blis and Factual) announced third-party integrations with advertising and analytics platforms, including Oracle, Salesforce/Einstein, IRI and others.
- Increase sales and field service impact and visits per trip by optimizing for customer value, recency of interaction and proximity to other customers.
- Prioritize new marketing opportunities by identifying underserved locations with characteristics which match best-performing territories.
- Understand buyer trends, high-value hotspots and performance down to a neighborhood or address.
Blis announced partnerships with Oracle Data Cloud, RSi’s Ansa, IRI and PushSpring. Blis advertising customers will use the third-party tools for targeting and insights:
- Targeting audiences: Blis customers will use Oracle Data Cloud to target audiences; Blis location data will be used for attribution.
- Measuring sales lift: RSi’s Ansa and IRI (both have POS data) will be able to report on the in-store sales impact for CPG and retail from digital ad exposures.
- PushSpring will enable targeting based on users’ app download histories (e.g., marketing to users of competitive apps).
Factual’s new “engine” SDK (software development kit) — which provides a wide range of location data attributes — is integrated with Oracle Responsys, Segment and Mixpanel for targeting and attribution. The company is also courting developers. Factual says that integrating the SDK will enable app developers to create improved and more contextualized user experiences:
Engine combines Factual’s industry-leading Global Places data with on-device location information and behavior patterns to help developers understand user context and identify the right moment to engage. Its machine learning algorithm takes into account factors including business operating hours, device usage patterns, speed and direction of travel to determine the specific circumstance of a user, beyond their location or place. By understanding and using these contextual factors, Engine enables apps to take the most accurate and appropriate action, ultimately improving engagement and user experience.
Location began as a relatively crude real-time mobile marketing tool and has evolved into a highly versatile cross-device targeting, personalization and attribution mechanism with an expanding array of use cases — as these announcements indicate.